# Visual Object Tracking on Multi-modal RGB-D Videos: A Review

arXiv: https://arxiv.org/abs/2201.09207 · HTML: https://mlsanity.com/paper/2201.09207/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 48 references that are in the map.
- First posted on arXiv 23 Jan 2022.

## Builds on (most cited first, 12 of 12)

- [Learning Discriminative Model Prediction for Tracking](https://mlsanity.com/paper/1904.07220/) (2019)
- [ATOM: Accurate Tracking by Overlap Maximization](https://mlsanity.com/paper/1811.07628/) (2018)
- [ECO: Efficient Convolution Operators for Tracking](https://mlsanity.com/paper/1611.09224/) (2016)
- [Siamese Network for RGB-D Salient Object Detection and Beyond](https://mlsanity.com/paper/2008.12134/) (2020)
- [DepthTrack : Unveiling the Power of RGBD Tracking](https://mlsanity.com/paper/2108.13962/) (2021)
- [NestFuse: An Infrared and Visible Image Fusion Architecture based on Nest Connection and Spatial/Channel Attention Models](https://mlsanity.com/paper/2007.00328/) (2020)
- [Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters](https://mlsanity.com/paper/1811.10863/) (2018)
- [CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark](https://mlsanity.com/paper/1907.00618/) (2019)
- [DAL -- A Deep Depth-aware Long-term Tracker](https://mlsanity.com/paper/1912.00660/) (2019)
- [Multi-focus Image Fusion using dictionary learning and Low-Rank Representation](https://mlsanity.com/paper/1804.08355/) (2018)
- [Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking](https://mlsanity.com/paper/1907.13242/) (2019)
- [Depth Masked Discriminative Correlation Filter](https://mlsanity.com/paper/1802.09227/) (2018)

## Built on by (most cited first, 5 of 5)

- [LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images](https://mlsanity.com/paper/2304.05172/) (2023)
- [CrossFuse: A Novel Cross Attention Mechanism based Infrared and Visible Image Fusion Approach](https://mlsanity.com/paper/2406.10581/) (2024)
- [SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning](https://mlsanity.com/paper/2204.00734/) (2022)
- [GrFormer: A Novel Transformer on Grassmann Manifold for Infrared and Visible Image Fusion](https://mlsanity.com/paper/2506.14384/) (2025)
- [RGB-D Tracking via Hierarchical Modality Aggregation and Distribution Network](https://mlsanity.com/paper/2504.17595/) (2025)

## Abstract (arXiv)

The development of visual object tracking has continued for decades. Recent years, as the wide accessibility of the low-cost RGBD sensors, the task of visual object tracking on RGB-D videos has drawn much attention. Compared to conventional RGB-only tracking, the RGB-D videos can provide more information that facilitates objecting tracking in some complicated scenarios. The goal of this review is to summarize the relative knowledge of the research filed of RGB-D tracking. To be specific, we will generalize the related RGB-D tracking benchmarking datasets as well as the corresponding performance measurements. Besides, the existing RGB-D tracking methods are summarized in the paper. Moreover, we discuss the possible future direction in the field of RGB-D tracking.